Artificial intelligence-driven approaches for materials design and discovery.
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| Title: | Artificial intelligence-driven approaches for materials design and discovery. |
|---|---|
| Authors: | Cheng M; Quantum Measurement Group, MIT, Cambridge, MA, USA. vipandyc@mit.edu.; Center for Computational Science and Engineering, MIT, Cambridge, MA, USA. vipandyc@mit.edu.; Department of Materials Science and Engineering, MIT, Cambridge, MA, USA. vipandyc@mit.edu., Fu CL; Quantum Measurement Group, MIT, Cambridge, MA, USA.; Department of Nuclear Science and Engineering, MIT, Cambridge, MA, USA., Okabe R; Quantum Measurement Group, MIT, Cambridge, MA, USA.; Department of Chemistry, MIT, Cambridge, MA, USA., Chotrattanapituk A; Quantum Measurement Group, MIT, Cambridge, MA, USA.; Department of Electrical Engineering and Computer Science, MIT, Cambridge, MA, USA., Boonkird A; Quantum Measurement Group, MIT, Cambridge, MA, USA.; Department of Nuclear Science and Engineering, MIT, Cambridge, MA, USA., Hung NT; Frontier Research Institute for Interdisciplinary Sciences, Tohoku University, Sendai, Japan., Li M; Quantum Measurement Group, MIT, Cambridge, MA, USA. mingda@mit.edu.; Center for Computational Science and Engineering, MIT, Cambridge, MA, USA. mingda@mit.edu.; Department of Nuclear Science and Engineering, MIT, Cambridge, MA, USA. mingda@mit.edu. |
| Source: | Nature materials [Nat Mater] 2026 Feb; Vol. 25 (2), pp. 174-190. Date of Electronic Publication: 2026 Jan 02. |
| Publication Type: | Journal Article; Review |
| Journal Info: | Publisher: Nature Pub. Group Country of Publication: England NLM ID: 101155473 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1476-4660 (Electronic) Linking ISSN: 14761122 NLM ISO Abbreviation: Nat Mater Subsets: MEDLINE; PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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